Adriano Dal Pastro
a5a61ac7e3
Espansione universo (su input utente "storico da cerbero"): il Cerbero MCP col token MAINNET serve Hyperliquid (230 perp REALI, storia nativa dal 2024). fetch_hyperliquid.py certifica 19 alt liquidi a 1d (flat 0%, cross-venue 4-9 bps vs Binance) -> data/raw/hl_*_1d.parquet. Abilita le strategie CROSS-SECTIONAL (impossibili a 2 asset). XS01 = cross-sectional momentum market-neutral (long 5 forti / short 5 deboli su ret 30g, ogni 10g, vol-target 20%). Validato onesto: plateau (config/k/subset), fee-robusto (0.3% RT), scorrelato a TP01 (-0.06), positivo OGNI anno 2024-26, meccanismo complementare (lavora nella dispersione quando TP01 e' in cash). Diverso dal regime-luck RV bocciato (19 asset, plateau, ogni anno+). Contributo al portafoglio (outer-join + pesi rinormalizzati per sleeve a date diverse): TP01-solo FULL 1.30 / HOLD 0.31 -> TP01 70% + XS01 30%: FULL 1.41 / HOLD 1.15, DD giu', ~ogni anno+. -> XS01 BATTE il portafoglio esistente: inserito in active_sleeves. Caveat (documentati): storia XS ~2.5 anni; STAT-MODE (book 19 gambe non eseguibile a 2k -> ~20k), sleeve diagnostico/forward-monitor. portfolio.combine ora outer-join+renorm. 12 test passano. Diario 2026-06-19-hyperliquid-xsec.md. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
70 lines
2.7 KiB
Python
70 lines
2.7 KiB
Python
"""Test del contenitore portafoglio estensibile."""
|
|
import sys
|
|
from pathlib import Path
|
|
PROJECT_ROOT = Path(__file__).resolve().parents[1]
|
|
sys.path.insert(0, str(PROJECT_ROOT))
|
|
import numpy as np
|
|
import pandas as pd
|
|
import pytest
|
|
|
|
from src.portfolio.portfolio import Sleeve, StrategyPortfolio, to_daily, metrics
|
|
|
|
|
|
def _const_sleeve(name, weight, val, n=400):
|
|
idx = pd.date_range("2020-01-01", periods=n, freq="1D", tz="UTC")
|
|
return Sleeve(name, weight, lambda: pd.Series(val, index=idx))
|
|
|
|
|
|
def test_single_sleeve_equals_itself():
|
|
s = _const_sleeve("A", 1.0, 0.001)
|
|
pf = StrategyPortfolio([s])
|
|
combo = pf.combined_daily()
|
|
assert np.allclose(combo.values, s.daily().values)
|
|
assert pf.weights() == {"A": 1.0}
|
|
|
|
|
|
def test_weights_normalize():
|
|
pf = StrategyPortfolio([_const_sleeve("A", 3.0, 0.001), _const_sleeve("B", 1.0, 0.002)])
|
|
w = pf.weights()
|
|
assert abs(sum(w.values()) - 1.0) < 1e-12
|
|
assert abs(w["A"] - 0.75) < 1e-12 and abs(w["B"] - 0.25) < 1e-12
|
|
|
|
|
|
def test_equal_weight_combine():
|
|
a, b = _const_sleeve("A", 1.0, 0.001), _const_sleeve("B", 1.0, 0.003)
|
|
pf = StrategyPortfolio([a, b])
|
|
combo = pf.combined_daily()
|
|
assert np.allclose(combo.values, 0.5 * 0.001 + 0.5 * 0.003) # 0.002
|
|
|
|
|
|
def test_to_daily_compounds_intraday():
|
|
# due barre da +1% nello stesso giorno -> +2.01% giornaliero
|
|
idx = pd.to_datetime(["2020-01-01T00:00", "2020-01-01T12:00"], utc=True)
|
|
d = to_daily(pd.Series([0.01, 0.01], index=idx))
|
|
assert len(d) == 1 and abs(d.iloc[0] - (1.01 * 1.01 - 1)) < 1e-12
|
|
|
|
|
|
def test_metrics_basic():
|
|
idx = pd.date_range("2020-01-01", periods=730, freq="1D", tz="UTC")
|
|
m = metrics(pd.Series(0.0005, index=idx)) # ritorno costante positivo
|
|
assert m["ret"] > 0 and m["maxdd"] == 0.0 and m["n"] == 730
|
|
|
|
|
|
def test_outer_join_renormalizes_late_sleeve():
|
|
# sleeve con date d'inizio diverse: prima parte A da solo (peso rinormalizzato a 1),
|
|
# poi A+B (pesi 0.7/0.3). Il portafoglio NON si tronca alla finestra comune.
|
|
idxA = pd.date_range("2020-01-01", periods=120, freq="1D", tz="UTC")
|
|
idxB = pd.date_range("2020-02-15", periods=60, freq="1D", tz="UTC")
|
|
A = Sleeve("A", 0.7, lambda: pd.Series(0.001, index=idxA))
|
|
B = Sleeve("B", 0.3, lambda: pd.Series(0.003, index=idxB))
|
|
combo = StrategyPortfolio([A, B]).combined_daily()
|
|
assert abs(combo.iloc[0] - 0.001) < 1e-12 # solo A -> 100% A
|
|
both = combo[combo.index >= idxB[0]]
|
|
assert abs(both.iloc[0] - (0.7 * 0.001 + 0.3 * 0.003)) < 1e-12 # blend rinormalizzato
|
|
assert len(combo) == 120 # span completo di A, non tronca
|
|
|
|
|
|
def test_empty_portfolio_raises():
|
|
with pytest.raises(ValueError):
|
|
StrategyPortfolio([])
|